Tag: Python

Why Must a Professional Learn Python?

Data Analytical languages or as they are popularly known, programming languages tend to be a little on the difficult side when it comes to learning them. Of all of them, it is believed that Python is one such language or tool, which is pretty easy to learn, especially when we compare it to the others. The syntax that this programming environment provides is not really that ceremonial and is quite easy to get a hang of. This helps all of those non-programmers work really efficiently in this software. When it comes to learning python or teaching it to someone, it is easier to do so with examples as opposed to teaching say Ruby or Perl mainly because of the lesser number of rules and special cases that Python has.

Many might have heard this name ‘Python’ for the very first time in the past couple of years. But what is interesting to know that this programming language has existed in the industry for the past 27 years, which is a lot more time. What then makes this tool so relevant in spite of being so old? It is the fact that Python can be pretty much applied to any and every software development or operations scenario that you can find in the world today. You can make use of python if you are looking to manage local and cloud infrastructure, or developing websites or have to work with SQL or even if you are looking for a custom function in order to make do with Pig or Hive, then Python applies there as well, this is a major reason as to why professionals especially those working in the analytical fields must learn python.

With python it is so easy that once you learn the language, you can very easily leverage the platform. It happens to be backed by PyPi which is pronounced as Pie Pie. Herein a user can make use of more than 85,000 modules as well as scripts. These modules are formulated in such a way that they are able to deliver pre-packaged functionality to any of the local python environments as well as solve a number of problems like the working of databases and the glitches therein, implementation of computer vision, and execution of advanced data analytics such as sentiment analysis or building of RESTful web services.

These days it has become quite a norm that any job you happen to be looking for, you will most probably be in need of having a skillset that is defined by big data and analytics which is why it becomes quite important for one to thoroughly understand the working of Python. As this data analytical tool happens to be a strong presence in the various areas of coding as well as data analytics it is sure to rule the roost in the near future. This is why we see a lot of professionals opting to learn Python from various professional training institutes like Imarticus Learning.

The inception of Python began in 1989 when its maker Guido van Rossum was irked by the weaknesses of ABC dialect (to be specific extensibility). Rossum began to take a shot at building up another programming language that incorporated every single great component of ABC dialect and new coveted elements, for example, extensibility and special case dealing with.

It is a programming language that is astoundingly simple to learn, and it can be utilized as a venturing stone into other programming dialects and structures. In case you’re an outright novice and this is your first time working with a coding language, that is something you unquestionably need.

Python is broadly utilized, including by various enormous organizations like Google, Pinterest, Instagram, Disney, Yahoo!, Nokia, IBM, and numerous others. The Raspberry Pi – which is a smaller than usual PC and DIY sweetheart’s fantasy – depends on Python as its fundamental programming dialect as well. You’re presumably asking why both of these things matter, and that is on account of once you learn Python, you’ll never have a deficiency of approaches to use the aptitude. Also, since a considerable measure of huge organizations depend on the dialect, you can take in substantial income as a Python engineer.

Different advantages of learning the Python language include:

1) Python can be utilized to create models, and rapidly on the grounds that it is so natural to work with and read.

2) Most computerization, information mining, and enormous information stages depend on Python. This is on account of it is the perfect dialect to work with for universally useful undertakings.

3) Python considers a more gainful coding condition than gigantic dialects like C# and Java. Experienced coders tend to remain more composed and beneficial when working with Python, also. Which is why you see a lot of data scientists opting for python certifications.

4) Python certification is anything but difficult to peruse, regardless of the possibility that you’re not a talented software engineer. Anybody can start working with python programming, all it takes is a touch of persistence and a considerable measure of practice. Additionally, this makes it a perfect possibility for use among multi-software engineer and substantial improvement groups.

5) Python powers Django, an entire and open source web application system. Structures – like Ruby on Rails – can be utilized to disentangle the advancement procedure.

6) It has a monstrous bolster base on account of the way that it is open source and group created. A huge number of similar designers work with the language every day and keep on improving centre usefulness. The most recent rendition of Python keeps on accepting upgrades and updates as time advances. This is an extraordinary approach to connect with different engineers.

When it comes to the best python online courses, there are very few institutes that you can actually go to. Imarticus Learning is one such institute which offers exceptionally industry endorsed Python programming courses online as well as offline. In addition to the python certification, these courses also help you put your best foot forward in terms of your career.

Hadoop is said to be an Apache.org project, which is adept at providing the distribution of software that processes large data sets, for a number of computer clusters, simply by using programming models. Hadoop is one such software, which is able to scale from a single computing system to close to thousands of commodity systems that are known to offer local storage and computer power. In a simpler sense, you can think of Hadoop as the 800 lb big data gorilla in the big data analytics space. This is one of the reasons why the use of this particular software programme is popular among data analysts.
On the other hand Spark, is known as the fast and general engine for large scale data processing, by Apache Spark developers. If we go on to compare these two programming environments, then where Hadoop happens to be the 800lb gorilla, Spark would be the 130 lb big data cheetah. Spark is cited to be way faster in terms of in-memory processing, when compared to Hadoop and MapReduce; but many believe that it may not be as fast when it comes to processing on disk space. What Spark actually excels at is effortlessly streaming of interactive queries, workloads and most importantly, machine learning.

While these two may be contenders, but time and again a lot of data analysts, have wanted the two programming environments to work together, on the same side. This is why a direct comparison kind of becomes a lot more difficult, as both of these perform the same functions and yet sometimes are able to perform entirely parallel functions. Come to think of it, if there were conclusions to be drawn, then it would be Hadoop that would be a better, more independently functioning network as Spark is known to depend on it, when it comes to file management.

While that may be the case, but there is one important thing to remember about both the networks. That is that there can never be an ‘either or’ scenario. This is mainly because they are not per say mutually exclusive of each other and neither of them can be a full replacement for the other. The one important similarity here is that the two are extremely compatible with each other, which is why their team makes for some really powerful solutions to a number of big data application issues.

There are a number of modules that work together and form a framework for Hadoop. Some of the primary ones are namely, Hadoop Common, Hadoop YARN, Hadoop Distributed File System (HDFS), and Hadoop MapReduce. While these happen to be some of the core modules, there are others as well like, Ambari, Avro, Cassandra, Hive, Pig, Ooziem Flume, and Sqoop and so on. The primary function of all of these modules is to further enhance the power of Hadoop and help extend it in to big data applications and larger data set processing. As majority of companies that deal with large data sets make use of Hadoop, it has gone on to become the de facto standard in the applications of big data. This is why a number of data aspirants turn to training institutes like Imarticus Learning, which offer comprehensive training of Hadoop.

India, as a country went through the biggest groundbreaking change in its economic history. With the ban on currency notes of higher denominations, a lot of Indians were left with no other option but to turn to Net Banking and online shopping. Many of us also noticed how a lot of websites, transformed into being very efficient and user friendly, while formulating a list of accurate recommendations for their buyers. Apart from that, the very famous company Paytm came to be in the mainstream, as the wallet for thousands of people, thus decreasing their woes of being cashless.

The digital space, functioned seamlessly, while chaos ensued on the more arbitrary space. Did any of you stop and wonder what the cause for this was? This was a very miniscule aspect of what is known to everyone as the field of Data Science. Have you ever noticed, how feedback forms today are no longer, just a formality. They have transformed into vital means, through which any internet based organization, is able to provide more customer centric services. Another example of how data science, came to the rescue of many was when, Google provided a link, which found the nearest ATM near you; during the cash crunch that existed in the past couple of weeks’ time. Have you wondered, who these digital magicians are, who have successfully made your life a little easier?

These aren’t any magicians, these are professionals adept in the knowledge of data analytics tools and are known as Data Scientists. They are the ones who extract meaningful data from the millions of records, that people create online through various websites and then perform analysis on all that data. These professionals then further, go on to predict the patterns of behavior of people, which may directly or indirectly influence the growth and prosperity of an organization. A Data Scientist has the role to analyze, study, massage and manage huge data sets, thereby improving the information flow to various organizations, in order to increase their business benefits.

There have been a number of studies and researches, all of which point to the fact that, Data Scientists are very much in demand, mainly due to the rapid growth of business domain in the e-commerce industry. But that is not it, Data Science as a field is also very sought after, in various other industries like aviation, stock market, health, military, social network, governmental services and so on. Apart from the growing demand for professionals in this domain, there is also the fact that Data Science as an industry provides great salary packages. Due to these reasons, Data Science as a job is seen as a very hot and emerging trend in today’s world; with even the Harvard Business announcing it as the ‘sexiest career’ of the 21st Century. This is one field where, the demand is only bound to increase in the near future and every organization would demand such trained individuals. Thus, so far there are no signs that this career would turn into a dying trend.

This has also prompted a lot of professionals to turn to various specialization courses so as to pursue their career in Data Science. Imarticus Learning is an institute, which has come to be among the more sought after institutes, due to its offerings in the data analytics domains. It provides a hands-on learning experience to the candidates, with its various courses in data analytics tools like SAS, R, Hadoop and Python and more.

Sound advice. You’d be forgiven to think this set of principles came from some dusty old philosophy manual. You’d be wrong. Believe it or not, this is an excerpt found on the FAQ page of the popular programming language, Python.

The Zen of Python is a collection of 20 software principles that influences the design of Python Programming Language. Long time Pythoneer Tim Peters succinctly channels the guiding principles for Python’s design into 20 aphorisms, only 19 of which have been written down. The 20th is left to your imagination.

The whole story behind Python is rather playful and whimsical. Guido van Rossum, the Dutch founder of the language, gave Python its name because he was reading the published scripts from Monty Python Flying Circus! Van Rossum was looking for a name that was short, unique, and mysterious, so he decided to call the language Python. Oh, and he developed the programming language during the Christmas holidays because he had nothing better to do.

Python is based on the English language – focused on simplicity. If C, C++ or Java would take 20 lines to implement something, Python takes around 3 – 4 lines to achieve the same thing. No weird symbols for simple code or variables, no need for semi colons, and code is always nicely spaced. Python enforces clean, structured programming techniques and borrows freely from other languages. It doesn’t enforce a single model or approach to solving a problem (so Zen-like!).

No wonder Python is snaking it’s way into programmers hearts — It is currently the second most popular programming language globally, after Java, and used by the likes of NYSE and Google.

Imarticus Learning offers online python certification. This is 100% Career Assistance program, our team provides a rigorous industry mentoring process that is customised to your needs. Additionally, the team conducts interview preparation sessions, resume building workshops, 1-1 mock interviews while also providing you access to our extensive corporate network and recruitment teams.